Entry requirements

120 credits including Automatic Control I. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

• determine relations between multivariable dynamic models in form of state space models and transfer functions
• analyse multivariable dynamic systems with respect to stability, sensitivity for disturbances, statistical properties, and controllability and observability
• analyse dynamic systems influenced by noise, and to determine stationary variances for given linear models
• design optimal observers (Kalman filters)
• design controllers for linear multivariable systems based on linear quadratic (LQ) control
• account for the principles behind model predictive control (MPC)
• evaluate controllers in laboratory work on real processes

Content

Mathematical description of linear multivariable systems in continuous and discrete time. Controllability and observability. Stability. Description of disturbances and their effects. Controller synthesis using linear quadratic theory and the separation theorem. Model predictive control.

Instruction

Lectures, problem solving sessions, tutorials and laboratory work. Guest lecture. Non-compulsory homework assignments.

Assessment

Written examination at the end of the course (4 credits). Passed laboratory course is also required (1 credit).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.